SAS Tricky Stuff

Tricky Stuff

After the interviewer is satisfied that you have used SAS to do a variety of things, you are likely to get some more substantial questions about SAS processing. These questions typically focus on some of the trickier aspects of the way SAS works, not because the interviewer is trying to trick you, but to give you a chance to demonstrate your knowledge of the details of SAS processing. At the same time, you can show how you approach technical questions and issues, and that is ultimately more important than your knowledge of any specific feature in SAS.

STOP statement

The processing of the STOP statement itself is ludicrously simple. However, when you explain the how and why of a STOP statement, you show that you understand:

• How a SAS program is divided into steps, and the difference between a data step and a proc step
• The automatic loop in the data step
• Conditions that cause the automatic loop to terminate, or to fail to terminate

RUN statement placement

The output of a program may be different based on whether a RUN statement comes before or after a global statement such as an OPTIONS or TITLE statement. If you are aware of this issue, it shows that you have written SAS programs that have more than the simplest of objectives. At the same time, your comments on this subject can also show that you know:

• The distinction between data step statements, proc step statements, and global statements
• How SAS finds step boundaries
• The importance of programming style

SUM or +

Adding numbers with the SUM function provides the same result that you get with the + numeric operator. For example, SUM(8, 4, 3) provides the same result as 8 + 4 + 3. Sometimes, though, you prefer to use the SUM function, and at other times, the + operator. As you explain this distinction, you can show that you understand:

• Missing values
• Propagation of missing values
• Treatment of missing values in statistical calculations in SAS
• Why it matters to handle missing values correctly in analytic processing
• The use of 0 as an argument in the SUM function to ensure that the result is not a missing value
• The performance differences between functions and operators
• Essential ideas of data cleaning

Statistics: functions vs. proc steps

Computing a statistic with a function, such as the MEAN function, is not exactly the same as computing the same statistic with a procedure, such as the UNIVARIATE procedure. As you explain this distinction, you show that you understand:

• The difference between summarizing across variables and summarizing across observations
• The statistical concept of degrees of freedom as it relates to the difference between sample statistics and population statistics, and the way this is implemented in some SAS procedures with the VARDEF= option

REPLACE= option

Many SAS programmers never have occasion to use the REPLACE= dataset option or system option, but if you are familiar with it, then you have to be aware of:

• The distinction between the input dataset and the output dataset in a step that makes changes in a set of data
• The general concept of name conflicts in programming theory
• Issues of programming style related to name conflicts
• How the system option compares to the corresponding dataset option

A question on this topic may also give you the opportunity to mention syntax check mode and issues of debugging SAS programs.

WHERE vs. IF

Sometimes, it makes no difference whether you use a WHERE statement or a subsetting IF statement. Sometimes it makes a big difference. In explaining this distinction, you have the opportunity to discuss:

• The distinction between data steps and proc steps
• The difference between declaration (declarative) statements and executable (action) statements
• The significance of the sequence of executable statements in a data step
• Some of the finer points of merging SAS datasets
• A few points of efficiency theory (although tests do not seem to bear the theory out in this case)
• The origin of the WHERE clause in SQL (of course, bring this up only if you’re good at SQL)
• WHERE operators that are not available in the IF statement or other data step statements

Compression

Compressing a SAS dataset is easy to to, so questions about it have more to do with determining when it is a good idea. You can weigh efficient use of storage space against efficient use of processing power, for example. Explain how you use representative data and performance measurements from SAS to test efficiency techniques, and you establish yourself as a SAS programmer who is ready to deal with large volumes of data. If you can explain why compression is effective in SAS datasets and observations larger than a certain minimum size and why binary compression works better than character compression for some kinds of data, then it shows you take software engineering seriously.

Macro processing

Almost the only reason interviewers ask about macros is to determine whether you appreciate the distinction between preprocessing and processing. Most SAS programmers are somewhat fuzzy about this, so if you have it perfectly clear in your mind, that makes you a cut about the rest — and if not, at least you should know that this is a topic you have to be careful about. There are endless technical issues with SAS macros, such as the system options that determine how much shows up in the log; your experience with this is especially important if the job involves maintaining SAS code written with macros.
SAS macro language is somewhat controversial, so be careful what you say of your opinion of it. To some managers, macro use is what distinguishes real SAS programmers from the pretenders, but to others, relying on macros all the time is a sure sign of a lazy, fuzzy-headed programmer. If you are pressed on this, it is probably safe to say that you are happy to work with macros or without them, depending on what the situation calls for.

Procedure vs. macro

The question, “What is the difference between a procedure and a macro?” can catch you off guard if it has never occurred to you to think of them as having anything in common. It can mystify you in a completely different way if you have thought of procedures and macros as interchangeable parts. You might mention:

• The difference between generating SAS code, as a macro usually does, and taking action directly on SAS data, as a procedure usually does
• What it means, in terms of efficiency, for a procedure to be a compiled program
• The drastic differences in syntax between a proc step and a macro call
• The IMPORT and EXPORT procedures, which with some options generate SAS statements much like a macro
• The %SYSFUNC macro function and %SYSCALL macro statement that allow a macro to take action directly on SAS data, much like a procedure

Scope of macro variables

If the interviewer asks a question about the scope of macro variables or the significance of the difference between local and global macro variables, the programming concept of scope is being used to see how you handle the new ways of thinking that programming requires. The possibility that the same name could be used for different things at different times is one of the more basic philosophical conundrums in computer programming. If you can appreciate the difference between a name and the object that the name refers to, then you can probably handle all the other philosophical challenges of programming.

Run groups

Run-group procedures are not a big part of base SAS, so a question about run-group processing and the difference between the RUN and QUIT statements probably has more to do with:

• What a procedure is
• What a step is
• All the work SAS has to go through as it alternately acquires a part of the SAS program from the execution queue, then executes that part of the program
• Connecting the program and the log messages

SAS date values

Questions about SAS date values have less to do with whether you have memorized the reference point of January 1, 1960, than with whether you understand the implications of time data treated as numeric values, such as:

• Using a date format to display the date variable in a meaningful way
• Computing a length of time by subtracting SAS date values

Efficiency techniques

With today’s bigger, faster computers, efficiency is a major concern only for the very largest SAS projects. If you get a series of technical questions about efficiency, it could mean one of the following:

• The employer is undertaking a project with an especially large volume of data
• The designated computer is not one of today’s bigger, faster computers
• The project is weighed down with horrendously inefficient code, and they are hoping you will be able to clean it all up

On the other hand, the interviewer may just be trying to gauge how well you understand the way SAS statements correspond to the actions the computer takes or how seriously you take the testing process for a program you write.

Debugger

Most SAS programmers never use the data step debugger, so questions about it are probably intended to determine how you feel about debugging — does the debugging process bug you, or is debugging one of the most essential things you do as a programmer?

Informats vs. formats

If you appreciate the distinction between informats and formats, it shows that:

• You can focus on details
• It doesn’t confuse you that two routines have the same name
• You have some idea of what is going on when a SAS program runs

TRANSPOSE procedure

The TRANSPOSE procedure has a few important uses, but questions about it usually don’t have that much to do with the procedure itself. The intriguing characteristic of the TRANSPOSE procedure is that input data values determine the names of output variables. The implication of this is that if the data values are incorrect, the program could end up with the wrong output variables. In what other ways does a program depend on having valid or correct data values as a starting point? What does it take to write a program that will run no matter what input data values are supplied?

_N_

Questions about the automatic variable _N_ (this might be pronounced “underscore N underscore” or just “N”) are meant to get at your understanding of the automatic actions of the data step, especially the automatic data step loop, also known as the observation loop.
A possible follow-up question asks how you can store the value of _N_ in the output SAS dataset. If you can answer this, it may show that you know the properties of automatic variables and know how to create a variable in the data step.

PUT function

A question about the PUT function might seem to be a trick question, but it is not meant to be. Beyond showing that you aren’t confused by two things as different as a statement and a function having the same name, your discussion of the PUT function can show:

• An understanding of what formats are
• Your experience in creating variables in data step statements
• A few of the finer points of SQL query optimization

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